Browsing Department of Information and Communication Technology by Subject "Machine learning"

Browsing Department of Information and Communication Technology by Subject "Machine learning"

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  • An Efficient Hybrid Model for Early Detection of Mango Leaf Pests 
    Sankeetha, V.; Agalya, V.; Vinoharan, V. (CSC-University of Jaffna, 2025)
    Mango is a vital cash crop widely cultivated across tropical and subtropical regions, including Sri Lanka, where it contributes significantly to agricultural income and rural livelihoods. However, mango cultivation is often ...
  • Fake News Detection Using Machine Learning 
    Edirisinghe, E.M.M.W.; Vinoharan, V. (Dept. of Computer Science, University of Jaffna, 2023)
    The spreading of fake news via diverse media is a major issue due to its potential to cause significant harmful impacts on society. Although social media is an emerging field offering various benefits, the reliability ...
  • Identification of Air-Writing Tamil Alphabetical Vowel Characters 
    Rukshani, P.; Senthooran, V. (Science and Information Organization, 2023)
    In recent years, there has been a lot of focus on gesture recognition because of its potential as a means of communication for cutting-edge gadgets. As a special category of gesture recognition, air-writing is the practice ...
  • Machine Learning for Effective Pest Detection in Mangifera indica (Mango) Crop Protection 
    Sankeetha, V.; Vinoharan, A.; Vinoharan, V. (IEEE, 2025)
    Mangifera indica, a key fruit crop in Sri Lanka, supports both agriculture and rural livelihoods but suffers significant losses from pest infestations. Early pest detection is crucial to reduce damage, yet manual inspection ...
  • Prediction of depression in social network posts using machine learning algorithms 
    Vithusha, B.; Akmal Jahan, M.A.C. (South Eastern University of Sri Lanka Oluvil, Sri Lanka, 2023)
    Depression is a serious mental disorder and its extreme or worst condition can lead to suicidal action. The number people who suffer from depression is drastically increasing day by day, particularly in teenagers who express ...
  • Sinhala-English Code-Mixed Corpus for Sentiment Analysis: Development and Baseline Evaluation 
    Perera, W.A.S.C.; Caldera, H.A. (IEEE, 2026)
    Language mixing and informal usage in code-mixed text make sentiment analysis a challenging task. Although a large number of linguistic resources are available for monolingual languages, lexicon and dataset resources are ...

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